code: def check_output_shape(self, model, num_classes):
      data = np.random.uniform(size=(2, 3, 224, 224))
      output = model(data, training=False)
      self.assertEqual(output.shape, (2, num_classes))
  
file_path: objax/tests/resnet_v2.py
imports: import unittest
  from parameterized import parameterized
  from functools import partial
  import numpy
  import tensorflow
  import objax
  from objax.zoo.resnet_v2 import ResNet18, ResNet34, ResNet50, ResNet101, ResNet152, ResNet200
  from objax.zoo.resnet_v2 import convert_keras_model, load_pretrained_weights_from_keras
label_desc: Use image node_id 2 for calling the TestResNetV2Pretrained obj's underlying member method code with example usage: obj.check_output_shape(model, num_classes) without return types